Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "62"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 62 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 54 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 52 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 62, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459869 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.014785 4.777214 16.044826 22.612182 3.903547 8.647672 1.104392 0.154313 0.6924 0.6944 0.3850 nan nan
2459868 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.048414 4.353997 24.905520 35.288954 1.411684 5.597175 0.802807 -2.499621 0.6698 0.6681 0.4040 nan nan
2459867 not_connected 100.00% 0.00% 0.00% 0.00% - - 1.694454 2.711765 20.066500 27.758832 1.260353 4.177637 0.494430 -2.161629 0.6781 0.6687 0.4066 nan nan
2459866 not_connected 100.00% 0.00% 0.00% 0.00% - - 2.145316 3.177244 18.730855 25.700238 1.568287 4.163355 0.452793 -1.721922 0.6826 0.6745 0.3992 nan nan
2459865 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.539884 3.193007 24.045263 33.032616 2.810967 7.314240 6.010273 5.430701 0.7043 0.6949 0.3694 nan nan
2459864 not_connected 100.00% 0.00% 0.00% 0.00% - - 8.167082 9.854640 24.127425 24.608589 5.103558 9.777687 -5.361813 -5.946592 0.6843 0.6572 0.4184 nan nan
2459863 not_connected 100.00% 0.00% 0.00% 0.00% - - 4.675380 5.740787 4.058566 4.039278 1.407123 3.253437 -3.024650 -3.881718 0.6825 0.6532 0.4077 nan nan
2459862 not_connected 100.00% 0.00% 0.00% 0.00% - - 6.560160 7.608337 29.083167 29.495201 7.336161 13.355751 -2.357111 -3.057696 0.6734 0.6908 0.4212 nan nan
2459861 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.577011 4.209099 2.745863 2.537770 0.403358 0.958682 -3.423381 -4.139777 0.6991 0.6689 0.4195 nan nan
2459860 not_connected 100.00% 0.00% 0.00% 0.00% - - 4.992019 5.758023 22.175601 22.515399 9.846846 16.173375 -2.608556 -3.481546 0.6996 0.6601 0.4189 nan nan
2459859 not_connected 0.00% 0.00% 0.00% 0.00% - - 3.417824 3.691690 2.823544 2.624930 0.680036 1.064734 -2.470989 -3.020278 0.7061 0.6652 0.4132 nan nan
2459858 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.494685 4.107617 2.536677 2.433311 0.426840 1.001561 -3.745448 -4.409988 0.7168 0.6727 0.4257 2.911843 2.589395
2459857 not_connected 100.00% 100.00% 100.00% 0.00% - - 15.624215 17.216216 6.228982 7.707841 6.323575 9.783461 1.627655 0.635604 0.0350 0.0370 0.0047 nan nan
2459856 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 6.846127 7.543441 20.323940 20.743450 4.237866 9.519693 -3.926204 -4.388749 0.7067 0.6862 0.4090 2.935196 2.409416
2459855 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 75.594207 75.379119 inf inf 4363.694470 4363.645964 4165.340837 4164.545046 0.0068 0.0064 0.0004 0.000000 0.000000
2459854 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.319463 4.255018 10.911993 13.673867 -0.172363 0.953329 -1.025255 -2.130159 0.7146 0.7433 0.4410 3.298856 2.880933
2459853 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.038282 2.789881 14.150397 17.316849 0.824885 4.137747 -1.025665 -2.886980 0.7283 0.6804 0.4344 3.939765 3.160674
2459852 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.731192 3.127974 13.761256 16.771258 5.836025 10.054203 9.655734 11.462341 0.8143 0.8194 0.2687 5.008961 4.838693
2459851 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.454775 5.049512 15.656150 18.066987 4.138855 20.610817 2.023042 12.244226 0.7437 0.7401 0.3546 3.161026 2.622893
2459850 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.449856 2.934137 13.397903 16.100141 1.847220 8.443309 0.022336 5.776343 0.7312 0.7518 0.3589 3.166085 2.969473
2459849 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.803269 4.390775 27.160216 32.949189 0.780759 4.613003 -1.084105 -2.433344 0.7295 0.7433 0.3659 3.949588 3.203119
2459848 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.769959 4.010204 19.462971 23.233181 2.279615 8.241565 -0.686365 -2.162525 0.7125 0.7486 0.3826 3.938115 3.124982
2459847 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.918800 3.460774 18.384147 21.656261 1.700908 6.478646 -0.000765 -1.778174 0.7156 0.6798 0.4379 7.559867 5.976017
2459846 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.679982 9.981952 14.574493 17.614556 8.251354 11.561971 -0.074927 -0.763383 0.8359 0.6624 0.5037 9.189733 4.121884
2459845 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.187996 5.245375 24.916510 30.470559 1.801563 6.397499 -0.199698 -2.874586 0.7410 0.7542 0.3675 0.000000 0.000000
2459844 not_connected 100.00% 100.00% 100.00% 0.00% - - 0.994023 5.030416 65.370515 70.654899 1.031227 1.460836 1.125008 -0.549334 0.0311 0.0334 0.0033 nan nan
2459843 not_connected 100.00% 0.66% 0.66% 0.00% 100.00% 0.00% 8.412020 9.765314 18.058582 18.870159 4.608402 9.914160 -3.090676 -3.757773 0.7385 0.7386 0.3919 3.142983 2.947175
2459842 not_connected 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.460814 1.157250 -0.284604 -0.522644 -2.101480 -1.969099 -1.939861 -2.161574 0.7339 0.6379 0.2748 3.049149 2.717842
2459841 not_connected 100.00% 100.00% 100.00% 0.00% - - 33.826922 40.616141 54.006353 61.944526 52.294359 53.143222 15.330640 12.055189 0.0332 0.0388 0.0064 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 62: 2459869

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 22.612182 3.014785 4.777214 16.044826 22.612182 3.903547 8.647672 1.104392 0.154313

Antenna 62: 2459868

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 35.288954 3.048414 4.353997 24.905520 35.288954 1.411684 5.597175 0.802807 -2.499621

Antenna 62: 2459867

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 27.758832 1.694454 2.711765 20.066500 27.758832 1.260353 4.177637 0.494430 -2.161629

Antenna 62: 2459866

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 25.700238 3.177244 2.145316 25.700238 18.730855 4.163355 1.568287 -1.721922 0.452793

Antenna 62: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 33.032616 3.539884 3.193007 24.045263 33.032616 2.810967 7.314240 6.010273 5.430701

Antenna 62: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 24.608589 9.854640 8.167082 24.608589 24.127425 9.777687 5.103558 -5.946592 -5.361813

Antenna 62: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Shape 5.740787 4.675380 5.740787 4.058566 4.039278 1.407123 3.253437 -3.024650 -3.881718

Antenna 62: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 29.495201 6.560160 7.608337 29.083167 29.495201 7.336161 13.355751 -2.357111 -3.057696

Antenna 62: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Shape 4.209099 4.209099 3.577011 2.537770 2.745863 0.958682 0.403358 -4.139777 -3.423381

Antenna 62: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 22.515399 4.992019 5.758023 22.175601 22.515399 9.846846 16.173375 -2.608556 -3.481546

Antenna 62: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Shape 3.691690 3.417824 3.691690 2.823544 2.624930 0.680036 1.064734 -2.470989 -3.020278

Antenna 62: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Shape 4.107617 4.107617 3.494685 2.433311 2.536677 1.001561 0.426840 -4.409988 -3.745448

Antenna 62: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Shape 17.216216 17.216216 15.624215 7.707841 6.228982 9.783461 6.323575 0.635604 1.627655

Antenna 62: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 20.743450 6.846127 7.543441 20.323940 20.743450 4.237866 9.519693 -3.926204 -4.388749

Antenna 62: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power inf 75.379119 75.594207 inf inf 4363.645964 4363.694470 4164.545046 4165.340837

Antenna 62: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 13.673867 4.255018 1.319463 13.673867 10.911993 0.953329 -0.172363 -2.130159 -1.025255

Antenna 62: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 17.316849 2.789881 1.038282 17.316849 14.150397 4.137747 0.824885 -2.886980 -1.025665

Antenna 62: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 16.771258 1.731192 3.127974 13.761256 16.771258 5.836025 10.054203 9.655734 11.462341

Antenna 62: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Temporal Variability 20.610817 1.454775 5.049512 15.656150 18.066987 4.138855 20.610817 2.023042 12.244226

Antenna 62: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 16.100141 1.449856 2.934137 13.397903 16.100141 1.847220 8.443309 0.022336 5.776343

Antenna 62: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 32.949189 1.803269 4.390775 27.160216 32.949189 0.780759 4.613003 -1.084105 -2.433344

Antenna 62: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 23.233181 4.010204 1.769959 23.233181 19.462971 8.241565 2.279615 -2.162525 -0.686365

Antenna 62: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 21.656261 3.460774 1.918800 21.656261 18.384147 6.478646 1.700908 -1.778174 -0.000765

Antenna 62: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 17.614556 7.679982 9.981952 14.574493 17.614556 8.251354 11.561971 -0.074927 -0.763383

Antenna 62: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 30.470559 5.245375 3.187996 30.470559 24.916510 6.397499 1.801563 -2.874586 -0.199698

Antenna 62: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 70.654899 0.994023 5.030416 65.370515 70.654899 1.031227 1.460836 1.125008 -0.549334

Antenna 62: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 18.870159 9.765314 8.412020 18.870159 18.058582 9.914160 4.608402 -3.757773 -3.090676

Antenna 62: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected ee Shape 1.460814 1.460814 1.157250 -0.284604 -0.522644 -2.101480 -1.969099 -1.939861 -2.161574

Antenna 62: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
62 N06 not_connected nn Power 61.944526 33.826922 40.616141 54.006353 61.944526 52.294359 53.143222 15.330640 12.055189
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